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# -*- coding: utf-8 -*-
# YAML-tagger:
# Type: kommune
# Status: finished
# Name: Oslo kommunes byrådsavdelinger og Rådhusets forvaltningstjeneste
# Format: HTML
# Datatype:
# Vendor:
# Run: daily
# Missingfields: journalseqnr, journalyear, journalid
# Publish duration: x months
import scraperwiki
import urllib
import urllib2
import lxml.html
import re
import resource
import dateutil.parser
import datetime
import sys
from dateutil.relativedelta import relativedelta
# Some example URLs
#http://byr-journal.cloudapp.net/Journal/SearchRelated?caseYear=2016&sequenceNumber=451
#http://byr-journal.cloudapp.net/Journal/Search?searchStringAdv=FromDate%3D01.09.2016,department%3DAll
#http://byr-journal.cloudapp.net/Journal/Search?searchStringAdv=FromDate%3D01.09.2016,ToDate%3D01.09.2016,department%3DAll
#http://byr-journal.cloudapp.net/Journal/Search/?querytype=and&offset=10
#http://byr-journal.cloudapp.net/Journal/Search/?querytype=and&FromDate=23.08.2016&ToDate=23.08.2016&offset=20
# http://byr-journal.cloudapp.net/Journal/Search?searchStringAdv=FromDate%3D23.08.2016,ToDate%3D23.08.2016,department%3DAll
scraperwiki.scrape("https://www.oslo.kommune.no/postjournal/")
postlistelib=scraperwiki.swimport('postliste-python-lib')
agency = u'Oslo kommune, Byrådsavdelingene'
baseurl = "http://www.oslo.kommune.no"
print "Fetching public journal for %s!" % agency
parser = postlistelib.JournalParser(agency=agency)
fieldmap = {
'Dokumentdato' : 'docdate',
'Dokumenttype' : 'doctype',
'Sak' : 'casedesc',
'Journaldato' : 'recorddate',
'Dato' : None, # Duplicate of recorddate
'Saksansvarlig' : 'saksansvarligenhet',
'Tilgangskode' : 'exemption',
'Fra' : 'sender',
'Til' : 'recipient',
'Til / Fra' : None, # Internal note, field empty
}
class NoDataEntries(LookupError):
pass
def cpu_spent():
usage = resource.getrusage(resource.RUSAGE_SELF)
return getattr(usage, 'ru_utime') + getattr(usage, 'ru_stime')
def cpu_available():
available = resource.getrlimit(resource.RLIMIT_CPU)[0]
# If no limit is set, assume 20 CPU seconds as the limit to avoid
# running for more than a few minutes every time.
if 0 > available:
available = 20
return available
def parse_day_html(parser, datastore, dayurl, html):
root = lxml.html.fromstring(html)
count = 0
for row in root.cssselect("div.document-rows"):
count = count + 1
data = {
'agency' : parser.agency,
'scrapedurl' : dayurl,
'scrapestamputc' : datetime.datetime.now()
}
head = row.cssselect("div.data-column div h3")[0].text_content().strip()
(arkivsaksref, docdesc) = head.split(" ", 1)
data['docdesc'] = docdesc
caseyear = 0
caseseqnr = 0
casedocseq = 0
caseid = 'unknown'
matchObj = re.match( r'(\d+)/(\d+)\s*-\s*(\d+)$', arkivsaksref, re.M|re.I)
if matchObj:
caseyear = int(matchObj.group(1))
data['caseseqnr'] = int(matchObj.group(2))
data['casedocseq'] = int(matchObj.group(3))
data['caseyear'] = caseyear
data['caseid'] = str(data['caseyear']) + "/" + str(data['caseseqnr'])
data['arkivsaksref'] = arkivsaksref
else:
print "error: really broken Arkivsaksnr: %s" % arkivsaksref
raise Exception("unable to parse url %s" % dayurl)
for tagclass in ['journal-recipients', 'journal-details']:
for d in row.cssselect("div.%s > dl" % tagclass):
field = d.cssselect("dt")[0].text_content().strip()
value = d.cssselect("dd")[0].text_content().strip()
if field in fieldmap:
if fieldmap[field] is not None: # Ignore duplicates
field = fieldmap[field]
else:
raise Exception("unknown field %s in %s" % (field, dayurl))
if value and '' != value:
data[field] = value
for field in ['docdate', 'recorddate']:
if field in data:
data[field] = dateutil.parser.parse(data[field],
dayfirst=True).date()
parser.verify_entry(data)
datastore.append(data)
# print data
return count
def fetch_day(parser, day):
datastore = []
daystr = day.strftime('%d.%m.%Y')
totalcount = 0
try:
offset = 0
offsetstep = 10
while True:
dayurl = "http://byr-journal.cloudapp.net/Journal/Search/?querytype=and&FromDate=%s&ToDate=%s&offset=%d" % (daystr, daystr, offset)
html = postlistelib.fetch_url_harder(dayurl).decode('utf-8')
# print html
count = parse_day_html(parser, datastore, dayurl, html)
totalcount = totalcount + count
# print count, dayurl
if 0 == count:
# print "Ending day at offset %d" % offset
break
offset = offset + offsetstep
scraperwiki.sqlite.save(unique_keys=['arkivsaksref'], data=datastore)
datastore = []
return totalcount
except scraperwiki.CPUTimeExceededError, e:
print "error: Ran out of time, abort scraping"
# Not saving, to avoid saving partial day. Better to scrape
# the entire day the next run.
return 0
except Exception, e:
# print html
print e
raise
aday = datetime.timedelta(1) # one day delta
newest = None
try:
newest = dateutil.parser.parse(scraperwiki.sqlite.select("max(recorddate) as max from swdata")[0]["max"], dayfirst=False).date()
oldest = dateutil.parser.parse(scraperwiki.sqlite.select("min(recorddate) as min from swdata")[0]["min"], dayfirst=False).date()
except scraperwiki.sqlite.SqliteError:
# Table not created yet, ignore the error
pass
if not newest:
# Bootstrap a month ago
newest = datetime.datetime.today() - aday * 30
oldest = newest
#print oldest, newest
skiplimit = 10
totalcount = 0
# Look forward one week to at least get past the weekends, rescan the
# last day in case new records showed up in the mean time. Next, scan
# backwards, one day before the oldest entry in the database.
for n in range(0, skiplimit, 1):
day = newest + aday * n
# print day
totalcount = totalcount + fetch_day(parser, day)
if cpu_spent() > (cpu_available() - 3):
print "Running short on CPU time, exiting"
sys.exit(0)
for n in range(-1, -skiplimit, -1):
day = oldest + aday * n
# print day
totalcount = totalcount + fetch_day(parser, day)
if cpu_spent() > (cpu_available() - 3):
print "Running short on CPU time, exiting"
sys.exit(0)
print "Fetched %d journal entries" % totalcount
# Need to rescan after a while to make sure we get the entries that
# take a while to show up when moving forward. Idea: Revisit all days
# where the record date is less than 30 days after the scraper date,
# allowing records to change for 30 days until we stop rescraping
# them. But wait 15 days before scraping again, to avoid scraping the
# same day over and over.
totalcount = 0
for drec in scraperwiki.sqlite.select("DISTINCT(recorddate) as d FROM swdata WHERE JULIANDAY(scrapestamputc) - JULIANDAY(recorddate) < 30 AND JULIANDAY('now') - JULIANDAY(scrapestamputc) > 15"):
day = dateutil.parser.parse(drec['d'], dayfirst=False).date()
print day
totalcount = totalcount + fetch_day(parser, day)
if cpu_spent() > (cpu_available() - 3):
print "Running short on CPU time, exiting"
sys.exit(0)
print "Rescanned %d journal entries" % totalcount
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